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Nendel, C., Kersebaum, K. C., Mirschel, W., & Wenkel, K. O. (2014). Testing farm management options as climate change adaptation strategies using the MONICA model. European Journal of Agronomy, 52, 47–56.
Abstract: Adaptation of agriculture to climate change will be driven at the farm level in first place. The MONICA model was employed in four different modelling exercises for demonstration and testing different management options for farmers in Germany to adjust their production system. 30-Year simulations were run for the periods 1996-2025 and 2056-2085 using future climate data generated by a statistical method on the basis of measured data from 1961 to 2000 and the A1B scenario of the IPCC (2007a). Crop rotation designs that are expected to become possible in the future due to a prolonged vegetation period and at the same time shortened cereal growth period were tested for their likely success. The model suggested that a spring barley succeeding a winter barley may be successfully grown in the second half of the century, allowing for a larger yields by intensification of the cropping cycle. Growing a winter wheat after a sugar beet may lead to future problems as late sowing makes the winter wheat grow into periods prone to drought. Irrigation is projected to considerably improve and stabilise the yields of late cereals and of shallow rooting crops (maize and pea) on sandy soils in the continental climate part of Germany, but not in the humid West. Nitrogen fertiliser management needs to be adjusted to increasing or decreasing yield expectations and for decreasing soil moisture. On soils containing sufficient amounts of Moisture and soil organic matter, enhanced mineralisation is expected to compensate for a greater N demand. (C) 2012 Elsevier B.V. All rights reserved.
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Bennetzen, E. H., Smith, P., & Porter, J. R. (2016). Agricultural production and greenhouse gas emissions from world regions—The major trends over 40 years. Glob. Environ. Change, 37, 43–55.
Abstract: Since 1970, global agricultural production has more than doubled with agriculture and land-use change now responsible for similar to 1/4 of greenhouse gas emissions from human activities. Yet, while greenhouse gas (GHG) emissions per unit of agricultural product have been reduced at a global level, trends in world regions have been quantified less thoroughly. The KPI (Kaya-Porter Identity) is a novel framework for analysing trends in agricultural production and land-use change and related GHG emissions. We apply this to assess trends and differences in nine world regions over the period 1970-2007. We use a deconstructed analysis of emissions from the mix of multiple sources, and show how each is changing in terms of absolute emissions on a per area and per produced unit basis, and how the change of emissions from each source contributes to the change in total emissions over time. The doubling of global agricultural production has mainly been delivered by developing and transitional countries, and this has been mirrored by increased GHG emissions. The decoupling of emissions from production shows vast regional differences. Our estimates show that emissions per unit crop (as kg CO2-equivalents per Giga Joule crop product), in Oceania, have been reduced by 94% from 1093 to 69; in Central & South America by 57% from 849 to 362; in sub-Saharan Africa by 27% from 421 to 309, and in Europe by 56% from 86 to 38. Emissions per unit livestock (as kg CO2-eq. GJ(-1) livestock product) have reduced; in sub-Saharan Africa by 24% from 6001 to 4580; in Central & South America by 61% from 3742 to 1448; in Central & Eastern Asia by 82% from 3,205 to 591, and; in North America by 28% from 878 to 632. In general, intensive and industrialised systems show the lowest emissions per unit of agricultural production. (C) 2016 Elsevier Ltd. All rights reserved.
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Waha, K., Müller, C., Bondeau, A., Dietrich, J. P., Kurukulasuriya, P., Heinke, J., et al. (2013). Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa. Glob. Environ. Change, 23(1), 130–143.
Abstract: Multiple cropping systems provide more harvest security for farmers, allow for crop intensification and furthermore influence ground cover, soil erosion, albedo, soil chemical properties, pest infestation and the carbon sequestration potential. We identify the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8600 households. We find that at least one sequential cropping system is traditionally used in 35% of all administrative units in the dataset, mainly including maize or groundnuts. We compare six different management scenarios and test their susceptibility as adaptation measure to climate change using the dynamic global vegetation model for managed land LPJmL. Aggregated mean crop yields in sub-Saharan Africa decrease by 6-24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. The crop yield decrease is typically weakest in sequential cropping systems and if farmers adapt the sowing date to changing climatic conditions. Crop calorific yields in single cropping systems only reach 40-55% of crop calorific yields obtained in sequential cropping systems at the end of the 21st century. The farmers’ choice of adequate crops, cropping systems and sowing dates can be an important adaptation strategy to climate change and these management options should be considered in climate change impact studies on agriculture. (C) 2012 Elsevier Ltd. All rights reserved.
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Waha, K., Müller, C., & Rolinski, S. (2013). Separate and combined effects of temperature and precipitation change on maize yields in sub-Saharan Africa for mid- to late-21st century. Global and Planetary Change, 106, 1–12.
Abstract: Maize (Zea mays L) is one of the most important food crops and very common in all parts of sub-Saharan Africa. In 2010 53 million tons of maize were produced in sub-Saharan Africa on about one third of the total harvested cropland area (similar to 33 million ha). Our aim is to identify the limiting agroclimatic variable for maize growth and development in sub-Saharan Africa by analyzing the separated and combined effects of temperature and precipitation. Under changing climate, both climate variables are projected to change severely, and their impacts on crop yields are frequently assessed using process-based crop models. However it is often unclear which agroclimatic variable will have the strongest influence on crop growth and development under climate change and previous studies disagree over this question. We create synthetic climate data in order to study the effect of large changes in the length of the wet season and the amount of precipitation during the wet season both separately and in combination with changes in temperature. The dynamic global vegetation model for managed land LPJmL is used to simulate maize yields under current and future climatic conditions for the two 10-year periods 2056-2065 and 2081-2090 for three climate scenarios for the A1b emission scenario but without considering the beneficial CO2 fertilization effect. The importance of temperature and precipitation effects on maize yields varies spatially and we identify four groups of crop yield changes: regions with strong negative effects resulting from climate change (<-33% yield change), regions with moderate (-33% to -10% yield change) or slight negative effects (-10% to +6% yield change), and regions with positive effects arising from climate change mainly in currently temperature-limited high altitudes (>+6% yield change). In the first three groups temperature increases lead to maize yield reductions of 3 to 20%, with the exception of mountainous and thus cooler regions in South and East Africa. A reduction of the wet season precipitation causes decreases in maize yield of at least 30% and prevails over the effect of increased temperatures in southern parts of Mozambique and Zambia, the Sahel and parts of eastern Africa in the two projection periods. This knowledge about the limiting abiotic stress factor in each region will help to prioritize future research needs in modeling of agricultural systems as well as in drought and heat stress breeding programs and to identify adaption options in agricultural development projects. On the other hand the study enhances the understanding of temperature and water stress effects on crop yields in a global vegetation model in order to identify future research and model development needs. (C) 2013 Elsevier B.V. All rights reserved.
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Leclère, D., Jayet, P. - A., & de Noblet-Ducoudré, N. (2013). Farm-level Autonomous Adaptation of European Agricultural Supply to Climate Change. Ecol. Econ., 87, 1–14.
Abstract: The impact of climate change on European agriculture is subject to a significant uncertainty, which reflects the intertwined nature of agriculture. This issue involves a large number of processes, ranging from field to global scales, which have not been fully integrated yet. In this study, we intend to help bridging this gap by quantifying the effect of farm-scale autonomous adaptations in response to changes in climate. To do so, we use a modelling framework coupling the STICS generic crop model to the AROPAj microeconomic model of European agricultural supply. This study provides a first estimate of the role of such adaptations, consistent at the European scale while detailed across European regions. Farm-scale autonomous adaptations significantly alter the impact of climate change over Europe, by widely alleviating negative impacts on crop yields and gross margins. They significantly increase European production levels. However, they also have an important and heterogeneous impact on irrigation water withdrawals, which exacerbate the differences in ambient atmospheric carbon dioxide concentrations among climate change scenarios. (c) 2012 Elsevier B.V. All rights reserved.
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